A business analyst reviews data on a computer
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Leveraging the Real-World Power of Data


Business Analytics

“Have you seen the Stat That commercials?” asks Dr. Marcus Ellis, Program Director of Norwich University’s Master of Science in Business Analytics. “It’s pretty much what we do.” Dr. Ellis explains that contrary to what some people might think, nearly every aspect of modern life, including football, is touched by the work that data analysts perform. And when paired with a business skillset, it can be a fascinating—and fun—way to make a living.

“When you visit the doctor and they ask you for your symptoms? They’re writing that down because they’re using a decision tree to figure out what your ailment might be. Have you ever wondered how Amazon gets your packages to you so quickly? Route optimization. This is what we do. Statistics and math and data science shouldn’t be scary words. They shouldn’t feel like four-letter words. They should feel like that is a field I want to get into.”

In the United States, however, the need for qualified data scientists—an umbrella term identifying a number of  professions related to the collection, analysis and interpretation of data—is expected to grow by more than 30 percent in the next decade, while the number of people pursuing those degrees is not keeping apace. Nearly a generation ago, Hal Varian, Google’s chief economist and a specialist in information economics, predicted that the job of statistician would become the “sexiest” around. According to The Economist magazine, Varian noted at the time that, while data are widely available, what is scarce is the ability to extract wisdom from them.

“Enterprises need people who know how to productize their output so it can be used in real-world use cases, not just people who can build an effective model,” TechRepublic stated recently on the data science skills gap.

Real-world use is the fundamental idea animating Norwich’s Master of Science in Business Analytics. The curriculum is designed to provide a comprehensive education in the skills, tools, and techniques they will need to succeed in a sophisticated, high-paced corporate environment. But it will also prepare students to tackle the everyday uses of data analysis, which are considerable—and immediately applicable to their current careers.

Dr. Ellis recounts the early days of what led him to teaching: his own graduate program was not using real-life, relatable examples, and the dean of his college invited him to make some suggestions that might ring truer.

“His response was, ‘Do you want to help us rewrite some of these examples?’” Dr. Ellis explained. “So I have taken that  approach with my students. If you don’t want an example about soccer stats or surfing or things that are interesting to me, what is interesting to you? Maybe you like NASCAR. Go find a NASCAR dataset and let’s do something cool with it. If you don't have that, bring something from work and let’s solve a problem and get you a promotion.”

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